Posts Tagged ‘analytics’

Big data requires extreme workloads

Read Using Big Data for Smarter Decision Making by Colin White.

Big data involves more than just the ability to handle large volumes of data. It also represents a wide range of new analytical technologies that opens up new business possibilities. But before reaping the rewards of big data analytics, there comes a set of challenges around deploying new technologies into existing data warehouse environments and providing systems that optimize computing performance for different workloads.

As I explored in my recent posts on smart consolidation, the data warehousing and analytics environment is more complex today than even just a few years ago. Many have found that mixing operational analytics and deep or advanced analytics on the same system brings significant challenges to performance and meeting SLAs. With operational analytics, business managers need continuous data ingest and fast access to standard reports with the ability to perform ad hoc queries that drill down into the data and provide new perspectives and insight. When a deep analytical query comes along that requires significant data volumes and extreme computing resources, operational query performance suffers. Big data adds yet another complexity around data sources, data quality, longevity of the data, and whether some of the big data should be integrated into the enterprise data warehouse for longer-term historical analysis.

The best way to handle these different types of workloads is to optimize systems to the workload, and combine these solutions with the enterprise data warehouse to create an “analytical environment”. We see many types of optimized systems in the market today – data warehouse appliances, data marts, noSQL systems, Hadoop-based systems, streaming data analytical systems, cloud-based solutions, etc., that complement (not replace) the enterprise data warehouse. Each system is optimized for a specific workload, and used together they can help streamline and provide fast response to a wide variety of business needs.

A majority of organizations today already understand this – really, optimizing computing resources to various types of data and associated workloads is nothing new. At some point in the data warehouse and analytical environment evolution, organizations reach a tipping point that drives separation of data and workloads. Data growth and new sources of (traditional) data, an increased number of users, increased complexity of queries, and “big data” are all drivers of this tipping point.

Colin White of BI Research wrote a white paper exploring new developments in data warehousing and analytics and the benefits that analyzing big data brings to the business. The paper also reinforces this notion of optimizing systems based on the types of data and workloads. The conclusion – integrating these systems together into a single analytics infrastructure drives smarter and faster business decisions. Read Using Big Data for Smarter Decision Making.

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Data will always lead information, always has, always will. Years ago, we created more data than we could analyze and understand at the time. Today, the same. Tomorrow, the same. The amount of data being created will always lead the ability to get information and understanding from it.

“Big data” is a leading edge description of having more data than can be processed into information, analyzed and understood. Many definitions of big data exist, let’s say 100TB or bigger for the sake of arguement. The volume, variety and velocity of data today is certainly accelerating, no question about that. But go back a couple of decades, and we could have made the same statements every year.

Leading companies in the big data space have solutions available today that can tap into an unprecedented amount of data. Petabyte-scale data warehouses, although not pervasive, are nothing new. Assembling the data is one thing, but analyzing it, presenting it and governing it is another. THE leading company has assembled a full “platform” covering the full breadth – operational analytics, deep / advanced analytics, predictive analytics, federated analytics, Hadoop analytics, streaming analytics… complete with end-to-end information governance.

Here is a sampling of big data use cases. Just skim through this and it’s sure to get your creative juices flowing on what CAN be done in your company. http://public.dhe.ibm.com/common/ssi/ecm/en/imc14715usen/IMC14715USEN.PDF 

Once you’ve skimmed through this, come back here and post your comments on 1) how you are currently using big data today, or 2) what you would like to use big data for.

And you know what? Years from now, the amount of data available will still outpace the ability to analyze it. At that time, will we call it “bigger data”?

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Well, I have to admit. Using the retail sales of high heeled shoes to indicate growth or a downturn in the economy is bit out there. But after seeing IBM in the news this week, I decided to look into this a bit further.

And they are right; the height of high heels sold does provide an indicator of the current economic situation. In an economic downturn, data shows that the height of high heels goes up – evidently, women buy higher heels in an attempt to escape the reality of tough economic times. Surely, feeling better about yourself, feeling prettier, perhaps a bit of personal indulgence, does help one escape the feeling of being controlled (can’t escape a bad job), beaten down (unemployed), and even trodden upon financially (foreclosed).

I have spoken about retail analytics a number of times in recent months, and I have been using a graph to open my presentation that shows the rise and dramatic fall of U.S.consumer spending as a wake up call to those analytically inclined. Consumer spending is such a key part of the U.S.economy and the retail industry. And as I wrote about in one of my earliest blog posts, in good economic times, everyone makes money. But in these tough economic times with consumer spending at a similar level to 1997 (mind you, after a fairly significant increase from its recent low), it takes much more than luck to survive let alone prosper. It takes an “analytics-driven” attitude to survive and thrive.

“This time…something different is happening – perhaps a mood of long term austerity is evolving among consumers sparking a desire to reduce ostentation in everyday settings.”

So what will happen later this week on “Black Friday?” Will consumer spending be strong – hitting the $20 Billion mark on Black Friday as analysts at MasterCard predict, or will it limp along like a wounded duck? Is there enough pent-up demand after consumers have cut back so much in recent months, or is there a bright future on the horizon for retailers? Will the sales, promotions and advertising make a difference? Will hot ticket items like the new Kindle Fire be strong performers? What will happen to retailers that don’t sell hot ticket items?

There are a lot of questions here…. One thing, however, is certain. Many retailers that rely on gut feel may not make it. But those that mined their data, that used predictive analytics, and that extended themselves to analyze the “big data” of social media, well…they may hit the proverbial nail on the head.

Let’s see what shakes in the upcoming days. Stay tuned for more….


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I coudn’t write a better blog posting than Larry Weber, one of my outstanding counterparts in evangelizing IBM Data Warehousing and Analytics solutions. So rather than write something different, I’d like to refer everyone over to Larry’s (the other Larry) blog to read more about our exciting new Smart Analytics System offerings and the Warehouse Packs Live demo that YOU can experience firsthand…on a tablet PC that a bunch of us will be carrying around the event. Come find one of us at the Data Management / Warehousing peds, or Demo Room, or BP Cafe, or in one of our countless business and technical sessions, or Ask The Expert and Birds of a Feather sessions, or Hands-On Labs, or…. Do you get the feel that we have A LOT going on at IOD 2011? Yes we do!! Come and see….!!

And READ Larry Weber’s blog! Ditto everything he says!


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Pay only for the data you analyze with InfoSphere Warehouse 9.7.3
Download this whitepaper

The new IBM InfoSphere Warehouse 9.7.3 offers a simple and transparent “pay for what you use” terabyte pricing that allows your organization to pay only for the volume of compressed user data you manage in your data warehouse. Download this whitepaper to learn how to build high-speed, scalable analytics into your data warehouse with InfoSphere Warehouse.

As your data volumes grow, you can purchase additional warehousing capacity on a just-in-time basis. IBM’s industry leading compression capabilities further increase the value of this new pricing option. Do what’s right for your business and your users – put the best warehouse software on the best machine for the job.

Now pay only for the data you analyze with the new InfoSphere Warehouse 9.7.3 and deliver powerful business insights. Download this whitepaper to learn how to build high-speed, scalable analytics into your data warehouse with InfoSphere Warehouse.

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No writing today, just  sharing a nice article on InformationWeek… http://www.informationweek.com/news/global-cio/interviews/showArticle.jhtml?articleID=229201238

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IBM’s Analytical Ways – Why Big Blue has invested $12 billion in data analytics.

Written at Forbes.com by Kym McNicholas, http://www.forbes.com/2010/11/05/data-analytics-ibm-technology-cio-network-jonas.html

In good economic climates, even a monkey on a rock can make money. In the tough times that we face today, you have to know your markets and your customers deeply in order to make better, faster and more confident decisions. This can only come from an integrated data warehouse based on trusted information, that is mined for trends, insights, opportunities and cost savings.

1 in 3 business leaders make decisions on information they do not have or do not trust, and 1 in 2 don’t have access to the information they need to do their jobs (IBM CIO Study 2010 – http://www-935.ibm.com/services/us/cio/ciostudy/executive-views.html).

So the New Year’s Resolution you must make, is to invest in providing your executives and Line of Business managers with the information and insights they need. And provide visual reports, scorecards and dashboards on key performance indicators.

You can bet that your competitors are fast at work doing this. Data warehousing and business analytics are more important in today’s global economy than ever before.

Once you have this insight, then and only then, can you take the right actions to optimize your business.

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